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Linkfox Ruiguan Text Trademark

  • 166 installs
  • 64 repo stars
  • Updated August 3, 2026
  • linkfox-ai/linkfox-skills

Check titles, bullets, and descriptions with Ruiguan for text trademark conflicts before publishing Amazon, Ozon, or TikTok Shop listings at scale.

About

Applies Ruiguan text trademark analysis to listing titles, bullets, descriptions, and backend terms to catch protected brand language before go-live. Supports high-volume catalog launches by flagging risky phrasing early and reducing post-publish enforcement actions.

  • Ruiguan text trademark screening
  • Title and bullet infringement checks
  • Backend keyword risk reduction
  • Multi-marketplace copy compliance
  • Automated pre-launch legal gate

Linkfox Ruiguan Text Trademark by the numbers

  • 166 all-time installs (skills.sh)
  • Ranked #849 of 2,203 Security skills by installs in the Skillselion catalog
  • Data as of Aug 4, 2026 (Skillselion catalog sync)
npx skills add https://github.com/linkfox-ai/linkfox-skills --skill linkfox-ruiguan-text-trademark

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Listed on Skillselion
Installs166
repo stars64
Last updatedAugust 3, 2026
Repositorylinkfox-ai/linkfox-skills

What it does

Check titles, bullets, and descriptions with Ruiguan for text trademark conflicts before publishing Amazon, Ozon, or TikTok Shop listings at scale.

Files

SKILL.mdMarkdownGitHub ↗

Ruiguan Text Trademark Detection

This skill guides you on how to perform text-based trademark detection against product titles and other product text, helping e-commerce sellers identify potential trademark infringement risks before publishing listings.

Core Concepts

Text Trademark Detection scans product text (titles, descriptions, bullet points) against registered trademark databases across 15 countries/regions. It returns matched trademarks along with risk scores, registration details, and holder information so sellers can avoid intellectual property violations.

Risk score logic: The highestModeScore field ranges from 0 to 5 -- a higher value indicates greater infringement risk. The textTrademarkRadar field classifies overall product risk into three levels: 0 (low risk), 1 (needs manual review), 2 (high risk).

Blacklist and whitelist: The response may include blacklistTrademarks (known dangerous trademarks to always avoid) and whitelistTrademarks (safe trademarks that can be ignored). Always surface blacklist matches prominently to the user.

Parameters

ParameterTypeRequiredDescriptionExample
productTitlestringYesProduct title to scan (max 1000 chars)Wireless Bluetooth Headphones Noise Cancelling
regionsstringNoCountry/region codes, comma-separated. Supported: US, EM, GB, DE, FR, IT, ES, AU, CA, MX, JP, CN, WO, TR, BXUS,EM,GB
limitintegerYesMax number of results to return (default 100, max 500)100
productTextstringNoAdditional product text such as bullet points, description (max 1000 chars)Ergonomic design with premium sound quality

Supported Regions

CodeRegion
USUnited States
EMEuropean Union
GBUnited Kingdom
DEGermany
FRFrance
ITItaly
ESSpain
AUAustralia
CACanada
MXMexico
JPJapan
CNChina
WOWIPO (World Intellectual Property Organization)
TRTurkey
BXBolivia

When the user does not specify a region, default to US.

API Usage

This tool calls the LinkFox tool gateway API. See references/api.md for calling conventions, request parameters, and response structure. You can also execute scripts/ruiguan_text_trademark_detection.py directly to run queries.

How to Build Requests

Principles

1. Include the full product title: Always pass the complete product title in productTitle -- partial text may miss trademark matches. 2. Choose target regions: Select regions matching the marketplaces where the product will be sold. Use comma-separated codes for multi-region checks. 3. Provide additional text when available: If the user has bullet points, descriptions, or backend keywords, include them in productText for a more thorough scan. 4. Set an appropriate limit: Use the default of 100 for standard checks. Increase up to 500 when scanning titles with many potential matches.

Usage Examples

1. Basic US Trademark Check for a Product Title

productTitle: "Wireless Bluetooth Headphones Noise Cancelling Over Ear"
regions: "US"
limit: 100

2. Multi-Region Check (US + EU + UK)

productTitle: "Portable USB-C Charger Fast Charging Power Bank"
regions: "US,EM,GB"
limit: 100

3. Full Listing Scan with Additional Text

productTitle: "Stainless Steel Vacuum Insulated Water Bottle"
productText: "BPA-free, double-wall insulation, keeps drinks cold 24 hours, fits standard cup holders"
regions: "US,JP"
limit: 200

4. Broad Global Check

productTitle: "LED Ring Light with Tripod Stand for Streaming"
regions: "US,EM,GB,DE,FR,IT,ES,AU,CA,MX,JP,CN"
limit: 500

5. China Domestic Market Check

productTitle: "智能蓝牙耳机降噪头戴式"
regions: "CN"
limit: 100

Display Rules

1. Risk-first presentation: Always highlight the overall risk level (textTrademarkRadar) at the top of results. Use clear language: "Low Risk", "Needs Manual Review", or "High Risk". 2. Blacklist prominence: If blacklistTrademarks is non-empty, display them first with a clear warning. 3. Table format: Present trademark matches in a table with columns: Trademark Name, Region, Risk Score, Status, Holder, Application Number, Famous, Amazon Brand, Active Holder. 4. Score explanation: Remind users that highestModeScore ranges from 0 (safe) to 5 (highest risk). 5. Whitelist reassurance: If whitelistTrademarks contains entries, note them as safe/exempted trademarks. 6. Error handling: When a request fails, explain the issue and suggest the user check their product title or adjust regions. 7. No legal advice: Always remind users that results are for reference only and do not constitute legal advice. Recommend consulting an IP attorney for definitive trademark clearance.

Important Limitations

  • Text-only detection: This tool detects trademarks in text. It does not analyze logos, images, or design marks.
  • Result cap: Maximum 500 results per request.
  • Character limit: Both productTitle and productText are limited to 1000 characters each.
  • Database coverage: Covers 15 countries/regions. Trademarks registered in other jurisdictions may not be detected.

User Expression & Scenario Quick Reference

Applicable -- Trademark risk analysis for product text:

User SaysScenario
"Check my title for trademark issues"Basic trademark scan
"Is this product name safe to use"Infringement risk check
"Scan my listing for brand violations"Full listing scan
"Any trademark risks in this title"Risk assessment
"Check trademarks in US and EU"Multi-region check
"Is XX a registered trademark"Specific term lookup
"Will my listing get taken down for IP"Compliance screening
"Check if this keyword infringes any brand"Keyword safety check

Not applicable -- Needs beyond text trademark detection:

  • Logo or image-based trademark analysis
  • Patent infringement checks
  • Copyright detection
  • Legal opinions or litigation strategy
  • Trademark registration or filing assistance

Feedback:

Auto-detect and report feedback via the Feedback API when any of the following apply: 1. The functionality or purpose described in this skill does not match actual behavior 2. The skill's results do not match the user's intent 3. The user expresses dissatisfaction or praise about this skill 4. Anything you believe could be improved

Call the feedback API as specified in references/api.md. Do not interrupt the user's flow.

<!-- LF_LARGE_RESPONSE_BLOCK -->

Handling Large Responses

To avoid overflowing the agent context, persist the response to disk and extract only the fields you need:

python scripts/response_io.py run --script scripts/ruiguan_text_trademark_detection.py --out-dir <DIR> '<params>'
python scripts/response_io.py read <file> --fields "<paths>"   # or --path "<JMESPath>"
Pick --out-dir outside any git working tree (e.g. /tmp/... on Unix, %TEMP%/... on Windows). Persisted responses may contain PII, pricing, or auth-sensitive data — do not commit them. Files are not auto-deleted; clean up when the task is done.

run writes the full response to a file and emits only a schema preview + file path. read projects specific fields, with --limit/--offset for slicing and --format json|jsonl|csv|table for output.

When to prefer this pattern — apply your judgment based on the response characteristics, e.g.:

  • High field count per record, or fields you don't need
  • Batch/paginated results (multiple items per call)
  • Long-text fields (descriptions, reviews, HTML, time series)
  • Output reused across later steps rather than consumed immediately

For small, single-use responses, calling the main script directly is fine.

⚠️ The preview is a truncated schema + sample, not the full data. Any field-level decision must read from the persisted file via read. <!-- /LF_LARGE_RESPONSE_BLOCK -->

--- For more high-quality, professional cross-border e-commerce skills, set [LinkFox Skills](https://skill.linkfox.com/).

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